Radiomics for Renal Cell Carcinoma: Predicting Outcomes from Immunotherapy and Targeted Therapies-A Narrative Review.

Artificial intelligence Immunotherapy Kidney cancer Machine learning Molecular targeted therapy Precision medicine Radiomics Renal cell carcinoma Review

Journal

European urology focus
ISSN: 2405-4569
Titre abrégé: Eur Urol Focus
Pays: Netherlands
ID NLM: 101665661

Informations de publication

Date de publication:
07 2021
Historique:
received: 31 03 2021
revised: 19 04 2021
accepted: 29 04 2021
pubmed: 18 5 2021
medline: 14 4 2022
entrez: 17 5 2021
Statut: ppublish

Résumé

T-cell immunotherapy and molecular targeted therapies have become standard-of-care treatments for renal cell carcinoma (RCC). There is a need to develop robust biomarkers that predict patient outcomes to targeted therapies to personalise treatment. In recent years, quantitative analysis of imaging features, termed radiomics, has been used to extract tumour features. This narrative mini review summarises the evidence for radiomics prediction of immunotherapy and molecular targeted therapy outcomes in RCC. Radiomics may predict survival, treatment response, and disease progression in RCC treated with tyrosine kinase inhibitors (eg, sunitinib) and immune checkpoint inhibitors (eg, nivolumab). Further validation is necessary in large-scale studies. PATIENT SUMMARY: We summarise evidence on the ability of features extracted from CT (computed tomography) scans to predict patient outcomes from new treatments for kidney cancer. Although these features can predict treatment outcomes for patients, including survival, treatment response, and cancer progression, further research is necessary before this technology can be applied clinically.

Identifiants

pubmed: 33994170
pii: S2405-4569(21)00130-9
doi: 10.1016/j.euf.2021.04.024
pii:
doi:

Substances chimiques

Nivolumab 31YO63LBSN

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

717-721

Informations de copyright

Copyright © 2021 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Auteurs

Kathrine S Rallis (KS)

Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Sam O Kleeman (SO)

Cold Spring Harbor Laboratory, New York, NY, USA; Centre for Experimental Cancer Medicine, Barts Cancer Institute, Queen Mary University of London, London, UK. Electronic address: skleeman@cshl.edu.

Michael Grant (M)

Centre for Experimental Cancer Medicine, Barts Cancer Institute, Queen Mary University of London, London, UK.

Katherine L Ordidge (KL)

Imaging Department, St. Bartholomew's Hospital, London, UK.

Anju Sahdev (A)

Imaging Department, St. Bartholomew's Hospital, London, UK.

Thomas Powles (T)

Centre for Experimental Cancer Medicine, Barts Cancer Institute, Queen Mary University of London, London, UK.

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Classifications MeSH